Abstract

To date, automatic handwring recognition systems are far from being perfect
and heavy human intervention is often required to check and correct the results
of such systems. In order to achieve correct transcriptions, human knowledge
can be integrated into the transcription process, following an Interactive
Predictive paradigm. We have recently proposed Mouse Actions as a significant
feedback information source for the underlying interactive system to improve
the poductivity of the human transcriptor. In this paper we review this way to
interact with the system and report comparative results using the publicly
available IAMDB dataset.